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<li class="navelem"><a class="el" href="../../d9/df8/tutorial_root.html">OpenCV Tutorials</a></li><li class="navelem"><a class="el" href="../../d9/d97/tutorial_table_of_content_features2d.html">2D Features framework (feature2d module)</a></li>  </ul>
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<div class="title">Harris corner detector </div>  </div>
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<div class="contents">
<div class="textblock"><p><b>Next Tutorial:</b> <a class="el" href="../../d8/dd8/tutorial_good_features_to_track.html">Shi-Tomasi corner detector</a></p>
<table class="doxtable">
<tr>
<th align="right"></th><th align="left"></th></tr>
<tr>
<td align="right">Original author </td><td align="left">Ana Huamán </td></tr>
<tr>
<td align="right">Compatibility </td><td align="left">OpenCV &gt;= 3.0 </td></tr>
</table>
<h2>Goal </h2>
<p>In this tutorial you will learn:</p>
<ul>
<li>What features are and why they are important</li>
<li>Use the function <a class="el" href="../../dd/d1a/group__imgproc__feature.html#gac1fc3598018010880e370e2f709b4345">cv::cornerHarris</a> to detect corners using the Harris-Stephens method.</li>
</ul>
<h2>Theory </h2>
<h3>What is a feature?</h3>
<ul>
<li>In computer vision, usually we need to find matching points between different frames of an environment. Why? If we know how two images relate to each other, we can use <em>both</em> images to extract information of them.</li>
<li>When we say <b>matching points</b> we are referring, in a general sense, to <em>characteristics</em> in the scene that we can recognize easily. We call these characteristics <b>features</b>.</li>
<li><b>So, what characteristics should a feature have?</b><ul>
<li>It must be <em>uniquely recognizable</em></li>
</ul>
</li>
</ul>
<h3>Types of Image Features</h3>
<p>To mention a few:</p>
<ul>
<li>Edges</li>
<li><b>Corners</b> (also known as interest points)</li>
<li>Blobs (also known as regions of interest )</li>
</ul>
<p>In this tutorial we will study the <em>corner</em> features, specifically.</p>
<h3>Why is a corner so special?</h3>
<ul>
<li>Because, since it is the intersection of two edges, it represents a point in which the directions of these two edges <em>change</em>. Hence, the gradient of the image (in both directions) have a high variation, which can be used to detect it.</li>
</ul>
<h3>How does it work?</h3>
<ul>
<li>Let's look for corners. Since corners represents a variation in the gradient in the image, we will look for this "variation".</li>
<li><p class="startli">Consider a grayscale image \(I\). We are going to sweep a window \(w(x,y)\) (with displacements \(u\) in the x direction and \(v\) in the y direction) \(I\) and will calculate the variation of intensity.</p>
<p class="formulaDsp">
\[E(u,v) = \sum _{x,y} w(x,y)[ I(x+u,y+v) - I(x,y)]^{2}\]
</p>
<p class="startli">where:</p><ul>
<li>\(w(x,y)\) is the window at position \((x,y)\)</li>
<li>\(I(x,y)\) is the intensity at \((x,y)\)</li>
<li>\(I(x+u,y+v)\) is the intensity at the moved window \((x+u,y+v)\)</li>
</ul>
</li>
<li><p class="startli">Since we are looking for windows with corners, we are looking for windows with a large variation in intensity. Hence, we have to maximize the equation above, specifically the term:</p>
<p class="formulaDsp">
\[\sum _{x,y}[ I(x+u,y+v) - I(x,y)]^{2}\]
</p>
</li>
<li><p class="startli">Using <em>Taylor expansion</em>:</p>
<p class="formulaDsp">
\[E(u,v) \approx \sum _{x,y}[ I(x,y) + u I_{x} + vI_{y} - I(x,y)]^{2}\]
</p>
</li>
<li><p class="startli">Expanding the equation and cancelling properly:</p>
<p class="formulaDsp">
\[E(u,v) \approx \sum _{x,y} u^{2}I_{x}^{2} + 2uvI_{x}I_{y} + v^{2}I_{y}^{2}\]
</p>
</li>
<li><p class="startli">Which can be expressed in a matrix form as:</p>
<p class="formulaDsp">
\[E(u,v) \approx \begin{bmatrix} u &amp; v \end{bmatrix} \left ( \displaystyle \sum_{x,y} w(x,y) \begin{bmatrix} I_x^{2} &amp; I_{x}I_{y} \\ I_xI_{y} &amp; I_{y}^{2} \end{bmatrix} \right ) \begin{bmatrix} u \\ v \end{bmatrix}\]
</p>
</li>
<li><p class="startli">Let's denote:</p>
<p class="formulaDsp">
\[M = \displaystyle \sum_{x,y} w(x,y) \begin{bmatrix} I_x^{2} &amp; I_{x}I_{y} \\ I_xI_{y} &amp; I_{y}^{2} \end{bmatrix}\]
</p>
</li>
<li><p class="startli">So, our equation now is:</p>
<p class="formulaDsp">
\[E(u,v) \approx \begin{bmatrix} u &amp; v \end{bmatrix} M \begin{bmatrix} u \\ v \end{bmatrix}\]
</p>
</li>
<li><p class="startli">A score is calculated for each window, to determine if it can possibly contain a corner:</p>
<p class="formulaDsp">
\[R = det(M) - k(trace(M))^{2}\]
</p>
<p class="startli">where:</p><ul>
<li>det(M) = \(\lambda_{1}\lambda_{2}\)</li>
<li>trace(M) = \(\lambda_{1}+\lambda_{2}\)</li>
</ul>
<p class="startli">a window with a score \(R\) greater than a certain value is considered a "corner"</p>
</li>
</ul>
<h2>Code </h2>
 <div class='newInnerHTML' title='cpp' style='display: none;'>C++</div><div class='toggleable_div label_cpp' style='display: none;'><p> This tutorial code's is shown lines below. You can also download it from <a href="https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/TrackingMotion/cornerHarris_Demo.cpp">here</a> </p><div class="fragment"><div class="line"></div><div class="line"><span class="preprocessor">#include &quot;<a class="code" href="../../d4/dd5/highgui_8hpp.html">opencv2/highgui.hpp</a>&quot;</span></div><div class="line"><span class="preprocessor">#include &quot;<a class="code" href="../../d1/d4f/imgproc_2include_2opencv2_2imgproc_8hpp.html">opencv2/imgproc.hpp</a>&quot;</span></div><div class="line"><span class="preprocessor">#include &lt;iostream&gt;</span></div><div class="line"></div><div class="line"><span class="keyword">using namespace </span><a class="code" href="../../d2/d75/namespacecv.html">cv</a>;</div><div class="line"><span class="keyword">using namespace </span>std;</div><div class="line"></div><div class="line"><a class="code" href="../../d3/d63/classcv_1_1Mat.html">Mat</a> src, src_gray;</div><div class="line"><span class="keywordtype">int</span> thresh = 200;</div><div class="line"><span class="keywordtype">int</span> max_thresh = 255;</div><div class="line"></div><div class="line"><span class="keyword">const</span> <span class="keywordtype">char</span>* source_window = <span class="stringliteral">&quot;Source image&quot;</span>;</div><div class="line"><span class="keyword">const</span> <span class="keywordtype">char</span>* corners_window = <span class="stringliteral">&quot;Corners detected&quot;</span>;</div><div class="line"></div><div class="line"><span class="keywordtype">void</span> cornerHarris_demo( <span class="keywordtype">int</span>, <span class="keywordtype">void</span>* );</div><div class="line"></div><div class="line"><span class="keywordtype">int</span> main( <span class="keywordtype">int</span> argc, <span class="keywordtype">char</span>** argv )</div><div class="line">{</div><div class="line">    <a class="code" href="../../d0/d2e/classcv_1_1CommandLineParser.html">CommandLineParser</a> parser( argc, argv, <span class="stringliteral">&quot;{@input | building.jpg | input image}&quot;</span> );</div><div class="line">    src = <a class="code" href="../../d4/da8/group__imgcodecs.html#ga288b8b3da0892bd651fce07b3bbd3a56">imread</a>( <a class="code" href="../../d6/dba/group__core__utils__samples.html#ga3a33b00033b46c698ff6340d95569c13">samples::findFile</a>( parser.get&lt;<a class="code" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a>&gt;( <span class="stringliteral">&quot;@input&quot;</span> ) ) );</div><div class="line">    <span class="keywordflow">if</span> ( src.<a class="code" href="../../d3/d63/classcv_1_1Mat.html#abbec3525a852e77998aba034813fded4">empty</a>() )</div><div class="line">    {</div><div class="line">        cout &lt;&lt; <span class="stringliteral">&quot;Could not open or find the image!\n&quot;</span> &lt;&lt; endl;</div><div class="line">        cout &lt;&lt; <span class="stringliteral">&quot;Usage: &quot;</span> &lt;&lt; argv[0] &lt;&lt; <span class="stringliteral">&quot; &lt;Input image&gt;&quot;</span> &lt;&lt; endl;</div><div class="line">        <span class="keywordflow">return</span> -1;</div><div class="line">    }</div><div class="line">    <a class="code" href="../../d8/d01/group__imgproc__color__conversions.html#ga397ae87e1288a81d2363b61574eb8cab">cvtColor</a>( src, src_gray, <a class="code" href="../../d8/d01/group__imgproc__color__conversions.html#gga4e0972be5de079fed4e3a10e24ef5ef0a353a4b8db9040165db4dacb5bcefb6ea">COLOR_BGR2GRAY</a> );</div><div class="line"></div><div class="line">    <a class="code" href="../../d7/dfc/group__highgui.html#ga5afdf8410934fd099df85c75b2e0888b">namedWindow</a>( source_window );</div><div class="line">    <a class="code" href="../../d7/dfc/group__highgui.html#gaf78d2155d30b728fc413803745b67a9b">createTrackbar</a>( <span class="stringliteral">&quot;Threshold: &quot;</span>, source_window, &amp;thresh, max_thresh, cornerHarris_demo );</div><div class="line">    <a class="code" href="../../d7/dfc/group__highgui.html#ga453d42fe4cb60e5723281a89973ee563">imshow</a>( source_window, src );</div><div class="line"></div><div class="line">    cornerHarris_demo( 0, 0 );</div><div class="line"></div><div class="line">    <a class="code" href="../../d7/dfc/group__highgui.html#ga5628525ad33f52eab17feebcfba38bd7">waitKey</a>();</div><div class="line">    <span class="keywordflow">return</span> 0;</div><div class="line">}</div><div class="line"></div><div class="line"><span class="keywordtype">void</span> cornerHarris_demo( <span class="keywordtype">int</span>, <span class="keywordtype">void</span>* )</div><div class="line">{</div><div class="line">    <span class="keywordtype">int</span> blockSize = 2;</div><div class="line">    <span class="keywordtype">int</span> apertureSize = 3;</div><div class="line">    <span class="keywordtype">double</span> k = 0.04;</div><div class="line"></div><div class="line">    <a class="code" href="../../d3/d63/classcv_1_1Mat.html">Mat</a> dst = <a class="code" href="../../d3/d63/classcv_1_1Mat.html#a0b57b6a326c8876d944d188a46e0f556">Mat::zeros</a>( src.<a class="code" href="../../d3/d63/classcv_1_1Mat.html#a146f8e8dda07d1365a575ab83d9828d1">size</a>(), <a class="code" href="../../d1/d1b/group__core__hal__interface.html#ga32ec76240e43e4c9c7b2e2785180a7e6">CV_32FC1</a> );</div><div class="line">    <a class="code" href="../../dd/d1a/group__imgproc__feature.html#gac1fc3598018010880e370e2f709b4345">cornerHarris</a>( src_gray, dst, blockSize, apertureSize, k );</div><div class="line"></div><div class="line">    <a class="code" href="../../d3/d63/classcv_1_1Mat.html">Mat</a> dst_norm, dst_norm_scaled;</div><div class="line">    <a class="code" href="../../dc/d84/group__core__basic.html#ga1b6a396a456c8b6c6e4afd8591560d80">normalize</a>( dst, dst_norm, 0, 255, <a class="code" href="../../d2/de8/group__core__array.html#ggad12cefbcb5291cf958a85b4b67b6149fa9f0c1c342a18114d47b516a88e29822e">NORM_MINMAX</a>, <a class="code" href="../../d1/d1b/group__core__hal__interface.html#ga32ec76240e43e4c9c7b2e2785180a7e6">CV_32FC1</a>, <a class="code" href="../../d3/d63/classcv_1_1Mat.html">Mat</a>() );</div><div class="line">    <a class="code" href="../../d2/de8/group__core__array.html#ga3460e9c9f37b563ab9dd550c4d8c4e7d">convertScaleAbs</a>( dst_norm, dst_norm_scaled );</div><div class="line"></div><div class="line">    <span class="keywordflow">for</span>( <span class="keywordtype">int</span> i = 0; i &lt; dst_norm.<a class="code" href="../../d3/d63/classcv_1_1Mat.html#abed816466c45234254d25bc59c31245e">rows</a> ; i++ )</div><div class="line">    {</div><div class="line">        <span class="keywordflow">for</span>( <span class="keywordtype">int</span> j = 0; j &lt; dst_norm.<a class="code" href="../../d3/d63/classcv_1_1Mat.html#aa3e5a47585c9ef6a0842556739155e3e">cols</a>; j++ )</div><div class="line">        {</div><div class="line">            <span class="keywordflow">if</span>( (<span class="keywordtype">int</span>) dst_norm.<a class="code" href="../../d3/d63/classcv_1_1Mat.html#aa5d20fc86d41d59e4d71ae93daee9726">at</a>&lt;<span class="keywordtype">float</span>&gt;(i,j) &gt; thresh )</div><div class="line">            {</div><div class="line">                <a class="code" href="../../d6/d6e/group__imgproc__draw.html#gaf10604b069374903dbd0f0488cb43670">circle</a>( dst_norm_scaled, <a class="code" href="../../dc/d84/group__core__basic.html#ga1e83eafb2d26b3c93f09e8338bcab192">Point</a>(j,i), 5,  <a class="code" href="../../dc/d84/group__core__basic.html#ga599fe92e910c027be274233eccad7beb">Scalar</a>(0), 2, 8, 0 );</div><div class="line">            }</div><div class="line">        }</div><div class="line">    }</div><div class="line"></div><div class="line">    <a class="code" href="../../d7/dfc/group__highgui.html#ga5afdf8410934fd099df85c75b2e0888b">namedWindow</a>( corners_window );</div><div class="line">    <a class="code" href="../../d7/dfc/group__highgui.html#ga453d42fe4cb60e5723281a89973ee563">imshow</a>( corners_window, dst_norm_scaled );</div><div class="line">}</div></div><!-- fragment -->  </div>  <div class='newInnerHTML' title='java' style='display: none;'>Java</div><div class='toggleable_div label_java' style='display: none;'><p> This tutorial code's is shown lines below. You can also download it from <a href="https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/TrackingMotion/harris_detector/CornerHarrisDemo.java">here</a> </p><div class="fragment"><div class="line"><span class="keyword">import</span> java.awt.BorderLayout;</div><div class="line"><span class="keyword">import</span> java.awt.Container;</div><div class="line"><span class="keyword">import</span> java.awt.Image;</div><div class="line"></div><div class="line"><span class="keyword">import</span> javax.swing.BoxLayout;</div><div class="line"><span class="keyword">import</span> javax.swing.ImageIcon;</div><div class="line"><span class="keyword">import</span> javax.swing.JFrame;</div><div class="line"><span class="keyword">import</span> javax.swing.JLabel;</div><div class="line"><span class="keyword">import</span> javax.swing.JPanel;</div><div class="line"><span class="keyword">import</span> javax.swing.JSlider;</div><div class="line"><span class="keyword">import</span> javax.swing.event.ChangeEvent;</div><div class="line"><span class="keyword">import</span> javax.swing.event.ChangeListener;</div><div class="line"></div><div class="line"><span class="keyword">import</span> org.opencv.core.Core;</div><div class="line"><span class="keyword">import</span> org.opencv.core.CvType;</div><div class="line"><span class="keyword">import</span> org.opencv.core.Mat;</div><div class="line"><span class="keyword">import</span> org.opencv.core.Point;</div><div class="line"><span class="keyword">import</span> org.opencv.core.Scalar;</div><div class="line"><span class="keyword">import</span> org.opencv.highgui.HighGui;</div><div class="line"><span class="keyword">import</span> org.opencv.imgcodecs.Imgcodecs;</div><div class="line"><span class="keyword">import</span> org.opencv.imgproc.Imgproc;</div><div class="line"></div><div class="line"><span class="keyword">class </span>CornerHarris {</div><div class="line">    <span class="keyword">private</span> Mat srcGray = <span class="keyword">new</span> Mat();</div><div class="line">    <span class="keyword">private</span> Mat dst = <span class="keyword">new</span> Mat();</div><div class="line">    <span class="keyword">private</span> Mat dstNorm = <span class="keyword">new</span> Mat();</div><div class="line">    <span class="keyword">private</span> Mat dstNormScaled = <span class="keyword">new</span> Mat();</div><div class="line">    <span class="keyword">private</span> JFrame frame;</div><div class="line">    <span class="keyword">private</span> JLabel imgLabel;</div><div class="line">    <span class="keyword">private</span> JLabel cornerLabel;</div><div class="line">    <span class="keyword">private</span> <span class="keyword">static</span> <span class="keyword">final</span> <span class="keywordtype">int</span> MAX_THRESHOLD = 255;</div><div class="line">    <span class="keyword">private</span> <span class="keywordtype">int</span> <a class="code" href="../../d7/d1b/group__imgproc__misc.html#gae8a4a146d1ca78c626a53577199e9c57">threshold</a> = 200;</div><div class="line"></div><div class="line">    <span class="keyword">public</span> CornerHarris(<a class="code" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a>[] args) {</div><div class="line">        <a class="code" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> filename = args.length &gt; 0 ? args[0] : <span class="stringliteral">&quot;../data/building.jpg&quot;</span>;</div><div class="line">        Mat src = Imgcodecs.imread(filename);</div><div class="line">        <span class="keywordflow">if</span> (src.empty()) {</div><div class="line">            System.err.println(<span class="stringliteral">&quot;Cannot read image: &quot;</span> + filename);</div><div class="line">            System.exit(0);</div><div class="line">        }</div><div class="line"></div><div class="line">        Imgproc.cvtColor(src, srcGray, Imgproc.COLOR_BGR2GRAY);</div><div class="line"></div><div class="line">        <span class="comment">// Create and set up the window.</span></div><div class="line">        frame = <span class="keyword">new</span> JFrame(<span class="stringliteral">&quot;Harris corner detector demo&quot;</span>);</div><div class="line">        frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);</div><div class="line">        <span class="comment">// Set up the content pane.</span></div><div class="line">        Image img = HighGui.toBufferedImage(src);</div><div class="line">        addComponentsToPane(frame.getContentPane(), img);</div><div class="line">        <span class="comment">// Use the content pane&#39;s default BorderLayout. No need for</span></div><div class="line">        <span class="comment">// setLayout(new BorderLayout());</span></div><div class="line">        <span class="comment">// Display the window.</span></div><div class="line">        frame.pack();</div><div class="line">        frame.setVisible(<span class="keyword">true</span>);</div><div class="line">        update();</div><div class="line">    }</div><div class="line"></div><div class="line">    <span class="keyword">private</span> <span class="keywordtype">void</span> addComponentsToPane(Container pane, Image img) {</div><div class="line">        <span class="keywordflow">if</span> (!(pane.getLayout() instanceof BorderLayout)) {</div><div class="line">            pane.add(<span class="keyword">new</span> JLabel(<span class="stringliteral">&quot;Container doesn&#39;t use BorderLayout!&quot;</span>));</div><div class="line">            <span class="keywordflow">return</span>;</div><div class="line">        }</div><div class="line"></div><div class="line">        JPanel sliderPanel = <span class="keyword">new</span> JPanel();</div><div class="line">        sliderPanel.setLayout(<span class="keyword">new</span> BoxLayout(sliderPanel, BoxLayout.PAGE_AXIS));</div><div class="line"></div><div class="line">        sliderPanel.add(<span class="keyword">new</span> JLabel(<span class="stringliteral">&quot;Threshold: &quot;</span>));</div><div class="line">        JSlider slider = <span class="keyword">new</span> JSlider(0, MAX_THRESHOLD, threshold);</div><div class="line">        slider.setMajorTickSpacing(20);</div><div class="line">        slider.setMinorTickSpacing(10);</div><div class="line">        slider.setPaintTicks(<span class="keyword">true</span>);</div><div class="line">        slider.setPaintLabels(<span class="keyword">true</span>);</div><div class="line">        slider.addChangeListener(<span class="keyword">new</span> ChangeListener() {</div><div class="line">            @Override</div><div class="line">            <span class="keyword">public</span> <span class="keywordtype">void</span> stateChanged(ChangeEvent e) {</div><div class="line">                JSlider source = (JSlider) e.getSource();</div><div class="line">                threshold = source.getValue();</div><div class="line">                update();</div><div class="line">            }</div><div class="line">        });</div><div class="line">        sliderPanel.add(slider);</div><div class="line">        pane.add(sliderPanel, BorderLayout.PAGE_START);</div><div class="line"></div><div class="line">        JPanel imgPanel = <span class="keyword">new</span> JPanel();</div><div class="line">        imgLabel = <span class="keyword">new</span> JLabel(<span class="keyword">new</span> ImageIcon(img));</div><div class="line">        imgPanel.add(imgLabel);</div><div class="line"></div><div class="line">        Mat blackImg = Mat.zeros(srcGray.size(), CvType.CV_8U);</div><div class="line">        cornerLabel = <span class="keyword">new</span> JLabel(<span class="keyword">new</span> ImageIcon(HighGui.toBufferedImage(blackImg)));</div><div class="line">        imgPanel.add(cornerLabel);</div><div class="line"></div><div class="line">        pane.add(imgPanel, BorderLayout.CENTER);</div><div class="line">    }</div><div class="line"></div><div class="line">    <span class="keyword">private</span> <span class="keywordtype">void</span> update() {</div><div class="line">        dst = Mat.zeros(srcGray.size(), CvType.CV_32F);</div><div class="line"></div><div class="line">        <span class="keywordtype">int</span> blockSize = 2;</div><div class="line">        <span class="keywordtype">int</span> apertureSize = 3;</div><div class="line">        <span class="keywordtype">double</span> k = 0.04;</div><div class="line"></div><div class="line">        Imgproc.cornerHarris(srcGray, dst, blockSize, apertureSize, k);</div><div class="line"></div><div class="line">        Core.normalize(dst, dstNorm, 0, 255, Core.NORM_MINMAX);</div><div class="line">        Core.convertScaleAbs(dstNorm, dstNormScaled);</div><div class="line"></div><div class="line">        <span class="keywordtype">float</span>[] dstNormData = <span class="keyword">new</span> <span class="keywordtype">float</span>[(int) (dstNorm.total() * dstNorm.channels())];</div><div class="line">        dstNorm.get(0, 0, dstNormData);</div><div class="line"></div><div class="line">        <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i &lt; dstNorm.rows(); i++) {</div><div class="line">            <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j &lt; dstNorm.cols(); j++) {</div><div class="line">                <span class="keywordflow">if</span> ((<span class="keywordtype">int</span>) dstNormData[i * dstNorm.cols() + j] &gt; <a class="code" href="../../d7/d1b/group__imgproc__misc.html#gae8a4a146d1ca78c626a53577199e9c57">threshold</a>) {</div><div class="line">                    Imgproc.circle(dstNormScaled, <span class="keyword">new</span> <a class="code" href="../../dc/d84/group__core__basic.html#ga1e83eafb2d26b3c93f09e8338bcab192">Point</a>(j, i), 5, <span class="keyword">new</span> <a class="code" href="../../dc/d84/group__core__basic.html#ga599fe92e910c027be274233eccad7beb">Scalar</a>(0), 2, 8, 0);</div><div class="line">                }</div><div class="line">            }</div><div class="line">        }</div><div class="line"></div><div class="line">        cornerLabel.setIcon(<span class="keyword">new</span> ImageIcon(HighGui.toBufferedImage(dstNormScaled)));</div><div class="line">        frame.repaint();</div><div class="line">    }</div><div class="line">}</div><div class="line"></div><div class="line"><span class="keyword">public</span> <span class="keyword">class </span>CornerHarrisDemo {</div><div class="line">    <span class="keyword">public</span> <span class="keyword">static</span> <span class="keywordtype">void</span> main(<a class="code" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a>[] args) {</div><div class="line">        <span class="comment">// Load the native OpenCV library</span></div><div class="line">        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);</div><div class="line"></div><div class="line">        <span class="comment">// Schedule a job for the event dispatch thread:</span></div><div class="line">        <span class="comment">// creating and showing this application&#39;s GUI.</span></div><div class="line">        javax.swing.SwingUtilities.invokeLater(<span class="keyword">new</span> Runnable() {</div><div class="line">            @Override</div><div class="line">            <span class="keyword">public</span> <span class="keywordtype">void</span> run() {</div><div class="line">                <span class="keyword">new</span> CornerHarris(args);</div><div class="line">            }</div><div class="line">        });</div><div class="line">    }</div><div class="line">}</div></div><!-- fragment -->  </div>  <div class='newInnerHTML' title='python' style='display: none;'>Python</div><div class='toggleable_div label_python' style='display: none;'><p> This tutorial code's is shown lines below. You can also download it from <a href="https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/TrackingMotion/harris_detector/cornerHarris_Demo.py">here</a> </p><div class="fragment"><div class="line"><span class="keyword">from</span> __future__ <span class="keyword">import</span> print_function</div><div class="line"><span class="keyword">import</span> cv2 <span class="keyword">as</span> cv</div><div class="line"><span class="keyword">import</span> numpy <span class="keyword">as</span> np</div><div class="line"><span class="keyword">import</span> argparse</div><div class="line"></div><div class="line">source_window = <span class="stringliteral">&#39;Source image&#39;</span></div><div class="line">corners_window = <span class="stringliteral">&#39;Corners detected&#39;</span></div><div class="line">max_thresh = 255</div><div class="line"></div><div class="line"><span class="keyword">def </span>cornerHarris_demo(val):</div><div class="line">    thresh = val</div><div class="line"></div><div class="line">    <span class="comment"># Detector parameters</span></div><div class="line">    blockSize = 2</div><div class="line">    apertureSize = 3</div><div class="line">    k = 0.04</div><div class="line"></div><div class="line">    <span class="comment"># Detecting corners</span></div><div class="line">    dst = <a class="code" href="../../dd/d1a/group__imgproc__feature.html#gac1fc3598018010880e370e2f709b4345">cv.cornerHarris</a>(src_gray, blockSize, apertureSize, k)</div><div class="line"></div><div class="line">    <span class="comment"># Normalizing</span></div><div class="line">    dst_norm = np.empty(dst.shape, dtype=np.float32)</div><div class="line">    <a class="code" href="../../d2/de8/group__core__array.html#ga7bcf47a1df78cf575162e0aed44960cb">cv.normalize</a>(dst, dst_norm, alpha=0, beta=255, norm_type=cv.NORM_MINMAX)</div><div class="line">    dst_norm_scaled = <a class="code" href="../../d2/de8/group__core__array.html#ga3460e9c9f37b563ab9dd550c4d8c4e7d">cv.convertScaleAbs</a>(dst_norm)</div><div class="line"></div><div class="line">    <span class="comment"># Drawing a circle around corners</span></div><div class="line">    <span class="keywordflow">for</span> i <span class="keywordflow">in</span> range(dst_norm.shape[0]):</div><div class="line">        <span class="keywordflow">for</span> j <span class="keywordflow">in</span> range(dst_norm.shape[1]):</div><div class="line">            <span class="keywordflow">if</span> int(dst_norm[i,j]) &gt; thresh:</div><div class="line">                <a class="code" href="../../d6/d6e/group__imgproc__draw.html#gaf10604b069374903dbd0f0488cb43670">cv.circle</a>(dst_norm_scaled, (j,i), 5, (0), 2)</div><div class="line"></div><div class="line">    <span class="comment"># Showing the result</span></div><div class="line">    <a class="code" href="../../d7/dfc/group__highgui.html#ga5afdf8410934fd099df85c75b2e0888b">cv.namedWindow</a>(corners_window)</div><div class="line">    <a class="code" href="../../df/d24/group__highgui__opengl.html#gaae7e90aa3415c68dba22a5ff2cefc25d">cv.imshow</a>(corners_window, dst_norm_scaled)</div><div class="line"></div><div class="line"><span class="comment"># Load source image and convert it to gray</span></div><div class="line">parser = argparse.ArgumentParser(description=<span class="stringliteral">&#39;Code for Harris corner detector tutorial.&#39;</span>)</div><div class="line">parser.add_argument(<span class="stringliteral">&#39;--input&#39;</span>, help=<span class="stringliteral">&#39;Path to input image.&#39;</span>, default=<span class="stringliteral">&#39;building.jpg&#39;</span>)</div><div class="line">args = parser.parse_args()</div><div class="line"></div><div class="line">src = <a class="code" href="../../d4/da8/group__imgcodecs.html#ga288b8b3da0892bd651fce07b3bbd3a56">cv.imread</a>(<a class="code" href="../../d6/dba/group__core__utils__samples.html#ga3a33b00033b46c698ff6340d95569c13">cv.samples.findFile</a>(args.input))</div><div class="line"><span class="keywordflow">if</span> src <span class="keywordflow">is</span> <span class="keywordtype">None</span>:</div><div class="line">    <a class="code" href="../../df/d57/namespacecv_1_1dnn.html#a701210a0203f2786cbfd04b2bd56da47">print</a>(<span class="stringliteral">&#39;Could not open or find the image:&#39;</span>, args.input)</div><div class="line">    exit(0)</div><div class="line"></div><div class="line">src_gray = <a class="code" href="../../d8/d01/group__imgproc__color__conversions.html#ga397ae87e1288a81d2363b61574eb8cab">cv.cvtColor</a>(src, cv.COLOR_BGR2GRAY)</div><div class="line"></div><div class="line"><span class="comment"># Create a window and a trackbar</span></div><div class="line"><a class="code" href="../../d7/dfc/group__highgui.html#ga5afdf8410934fd099df85c75b2e0888b">cv.namedWindow</a>(source_window)</div><div class="line">thresh = 200 <span class="comment"># initial threshold</span></div><div class="line"><a class="code" href="../../d7/dfc/group__highgui.html#gaf78d2155d30b728fc413803745b67a9b">cv.createTrackbar</a>(<span class="stringliteral">&#39;Threshold: &#39;</span>, source_window, thresh, max_thresh, cornerHarris_demo)</div><div class="line"><a class="code" href="../../df/d24/group__highgui__opengl.html#gaae7e90aa3415c68dba22a5ff2cefc25d">cv.imshow</a>(source_window, src)</div><div class="line">cornerHarris_demo(thresh)</div><div class="line"></div><div class="line"><a class="code" href="../../d7/dfc/group__highgui.html#ga5628525ad33f52eab17feebcfba38bd7">cv.waitKey</a>()</div></div><!-- fragment -->  </div> <h2>Explanation </h2>
<h2>Result </h2>
<p>The original image:</p>
<div class="image">
<img src="../../Harris_Detector_Original_Image.jpg" alt="Harris_Detector_Original_Image.jpg"/>
</div>
<p>The detected corners are surrounded by a small black circle</p>
<div class="image">
<img src="../../Harris_Detector_Result.jpg" alt="Harris_Detector_Result.jpg"/>
</div>
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